## $`1`
## [1] 1 3 7 11 15 17 19 21 22 33 36 38 39 40 41 43 47 52
## [19] 53 59 60 61 65 68 71 75 80 87 90 95 96 100 103 106 107 111
## [37] 117 128 131 132 137 138 147 149 150 151 164 165 168 170 174 175 177 178
## [55] 180 181 187 188 192 193 194 198 199 205 212 213 214 219 223 230 231 234
## [73] 237 239 245 255 257 258 259 264 267 269 270 272 280 281 283 284 287 288
## [91] 291 292 298 300 301 302 305 306 310 314 318 320 322 325 328 329 331 332
## [109] 337 340 344 346 347 348 352 353 356 359 379 382 384 388 389 390 391 396
## [127] 400 407 412 416 417 418 419 420 426 428 429 430 431 432 433 437
##
## $`2`
## [1] 2 4 5 9 24 25 26 30 31 44 46 50 56 57 62 66 67 70 76
## [20] 77 78 83 88 92 104 105 110 112 126 130 148 157 158 162 163 167 171 176
## [39] 185 189 190 196 201 203 210 215 217 220 226 227 228 235 236 238 242 248 265
## [58] 271 273 274 282 289 290 293 294 295 303 311 327 330 334 336 338 339 342 345
## [77] 349 350 351 364 366 369 372 373 374 385 394 403 409 411 415 427 435
##
## $`3`
## [1] 6
##
## $`4`
## [1] 8 14 54 55 69 102 119 135 216 397
##
## $`5`
## [1] 10 127 133 355 425
##
## $`6`
## [1] 12 18 29 45 86 93 98 109 115 120 134 140 143 144 145 152 169 179 182
## [20] 183 200 206 218 232 241 244 247 251 256 261 275 279 308 317 323 333 335 358
## [39] 360 365 375 380 383 386 399 413 414 434
## gn.membership
## Min. : 1.00
## 1st Qu.: 1.00
## Median : 2.00
## Mean :10.47
## 3rd Qu.: 8.00
## Max. :77.00
## $`1`
## [1] 82 278
##
## $`2`
## [1] 18 23 29 45 79 86 93 97 98 99 109 115 120 124 134 140 143 146 152
## [20] 169 179 182 200 202 206 211 218 226 232 241 244 247 261 268 275 279 285 296
## [39] 308 317 323 333 358 360 365 375 378 380 383 386 399 409 413 414 418 422 434
##
## $`3`
## [1] 4 5 9 21 24 25 30 31 42 44 46 52 56 62 66 67 70 71 76
## [20] 78 92 104 110 112 126 128 131 135 156 157 158 163 175 176 185 189 190 193
## [39] 196 201 203 217 220 227 235 236 238 242 248 255 259 265 269 271 274 284 290
## [58] 293 294 295 303 314 320 322 336 339 342 351 364 366 369 372 374 403 415 431
## [77] 435
##
## $`4`
## [1] 94 101 231 362
##
## $`5`
## [1] 8 16 17 32 34 40 47 51 54 55 57 58 64 69 80 84 102 113 114
## [20] 116 119 121 122 125 129 141 142 153 154 155 159 162 166 171 173 186 195 197
## [39] 209 216 222 246 249 263 266 276 277 286 299 307 312 313 316 321 324 332 343
## [58] 349 361 367 371 373 376 387 394 397 401 411 436
##
## $`6`
## [1] 27 35 381
## walk.membership
## Min. : 1.000
## 1st Qu.: 3.000
## Median : 7.000
## Mean : 9.732
## 3rd Qu.: 8.000
## Max. :66.000
The Girvan-Newman algorithm found 77 total groups whereas the Random Walk algorithm found 66. Let’s look at the correlation between the membership groups of each algorithm:
## gn.membership walk.membership
## gn.membership 1.0000000 0.8270279
## walk.membership 0.8270279 1.0000000
The correlation coefficient between the two algorithms is positive and pretty high at 0.83; the two algorithm divide the nodes into pretty similar groups.
## [1] 0.7129782
It is not a perfect match but the two algorithms are dividing the nodes into pretty similar groups as the value of 0.713 is pretty high.
I will explore the attributes and see how the Grivan-Newman community detection algorithm relates to the gender and year of the students/nodes.
This visualization adds different colors to the nodes for the year they are graduating. There seem to be some grouping that seems congruent with the year the student is in. For example, most of the students graduating in 2008 seem to be more or less in the same groups. Same with the students graduating in 2006. There definitely seem to be a lot of connections between students across the graduating years. We have the least number of nodes for students graduating in 2005- these nodes seem to not be grouped together based on their year of graduation.
Based on this visualization, it seems that there seems to be some clustering of the nodes based on their gender, especially in the middle with the most connected nodes. Just by looking at the visualization, it is hard to say whether the gender influences the grouping too much. We see a mix of cross-gender friendship groups as well as same-gender friendships in both small and big groups. There definitely are some bigger groupings that have mostly one gender.